Triple
T193981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of the Red Banner |
E3778
|
entity |
| Predicate | multipleAwardsIndicatedBy |
P219
|
FINISHED |
| Object | additional badges |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: additional badges | Statement: [Order of the Red Banner, multipleAwardsIndicatedBy, additional badges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: multipleAwardsIndicatedBy Context triple: [Order of the Red Banner, multipleAwardsIndicatedBy, additional badges]
-
A.
numberOfAwards
Indicates the total count of awards that have been received by an entity.
-
B.
relatedAward
chosen
Indicates that there is an award connected or associated with the subject entity, such as an honor, prize, or recognition related to it.
-
C.
awardReceived
Indicates that an entity has been granted or honored with a specific award or recognition.
-
D.
awardGivenBy
Indicates that an award is conferred or presented by one entity to another.
-
E.
awardsTitle
Indicates that an entity confers or grants a specific title or honorific designation to another entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a2596810c48190ab687c0c2efaa9e2 |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a256769ad8819083c1d83082c0215e |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.